Method for calculating dielectric versus air void content relationship for asphalt concrete using a single calibration measurement

ABSTRACT

A method for generating a calibration curve of asphalt concrete of a known mix. Initially, a single sample of the known asphalt concrete mix is obtained. The single sample has a known percent voids. A dielectric measurement of the single sample is obtained. Using only the dielectric measurement of the single sample, the sample&#39;s known percent voids, and a dielectric of air, a theoretical ideal dielectric for the asphalt concrete mix at 0% voids is computed. A dielectric vs. percent voids calibration curve is generated based on the computed ideal dielectric.

FIELD OF THE DISCLOSED TECHNOLOGY

The disclosed technology relates generally to methods for computingcompaction of asphalt concrete, and, more specifically, to a method tocalculate an amount of compaction of asphalt concrete based only on asingle calibration measurement.

BACKGROUND OF THE DISCLOSED TECHNOLOGY

There is a need to easily and accurately know the density of a newasphalt road as it is being placed, since controlling its density candouble the life of the road. Ground Penetrating Radar (GPR) technologyis often used to measure the effective dielectric of asphalt on roadsurfaces. Knowledge of the effective dielectric of asphalt is useful incalculating the density of the asphalt, or, more accurately, its airvoid content. Once a calibration curve is created that maps dielectricto air void content, the density can be known simply by measuring thedielectric value at a location on the road.

In the prior art, the relationship between dielectric and air voidcontent is typically determined by obtaining several asphalt samples,usually about 6 inches in diameter and a 2-4 inches thick. By using afew such samples at different air void contents, either drilled from theroad (Cores) or created in the lab (Pucks), and by measuring both thedielectric and the air void content of each sample, a curve that mapsthe two measurements to each other can be calculated. Although useful,this prior art method is laborious, since calibration curves, requiringperhaps 10 cores, are required for hundreds of asphalt mix designs usedfor paving operations. Furthermore, a mix design selected for a pavingproject often needs to be adjusted, for example due to changes in thetemperature or the ambient moisture (e.g. rain), requiring frequentcurve calculations. Daily regeneration of calibration curves isburdensome, since a lab technician must create multiple asphalt samplesand measure the densities and dielectrics of such samples each timeconditions change.

There is thus a need in the art for an easy method of calibrating thedielectric and air void content of asphalt, preferably using fewersamples and/or regeneration times.

SUMMARY OF THE DISCLOSED TECHNOLOGY

The disclosed technology relates generally to methods for computingcompaction of asphalt concrete, and, more specifically, to a method tocalculate densities that needs only a single calibration measurement tocreate a calibration curve. This has implications not only for savingtime and money, but more importantly saving lives, since reducing thenumber of cores needed reduces the hazards associated with collectingthem.

This disclosure should be interpreted according to the definitionsbelow. In case of a contradiction between the definitions in thisDefinitions section and other sections of this disclosure, this sectionshould prevail.

Dielectric—an electromagnetic property that relates to the ability of amaterial to store energy in the presence of an electric field.

Effective Dielectric—an average dielectric of a micro-inhomogeneousmedium, i.e. a medium whose dielectric is not homogeneous on a smallscale.

Asphalt—a composite material comprising and having, typically, at least90% aggregate (i.e. rock fragments) and bitumen, and, in some cases,also including additional materials. Also known as “Pavement” in NorthAmerica and as “asphalt concrete” in technical papers, these terms areused interchangeably.

Dielectric Mixing Equation—an equation that calculates the effectivedielectric of a dielectrically inhomogeneous medium, given volumepercentages and dielectrics of constituents in the medium.

Asphalt Air Void Content—The percentage or volume ratio of air in anasphalt sample.

Bitumen—a black viscous mixture of hydrocarbons obtained naturally or asa residue from petroleum distillation. Bitumen is commonly used as aconstituent in asphalt concrete. It may also be called tar or binder.

Aggregate—rock and sand constituents typically included in asphaltconcrete. Aggregates may be taken from nearby quarries, and as such havehighly regional material properties (shape, density, dielectric,porosity etc.).

Air Void—Air trapped inside asphalt concrete. The air void is typicallyexpressed as a percentage of the total volume of asphalt concrete.

Puck—a cylindrical-shaped asphalt sample that is typically compacted toa pre-determined amount using gyratory compactor (and thus typically hasa known and predetermined air void percentage).

Percent Compaction—a term used in relation to asphalt paving operations.A sample of asphalt that has one hundred percent compaction contains noair voids. Consequently, percent compaction is calculated from % Voidsusing the relation: % Compaction=100−% Voids.

Magnetic Permeability—an electromagnetic property that relates themagnetic induction inside a material to the magnetic field intensity.

Mix Design—a particular combination of aggregate, bitumen and possiblyother constituents that are mixed together to make asphalt. Differentmix designs are customized for the locations where the asphalt is to beused.

In accordance with an embodiment of the disclosed technology, there isprovided a novel method for generating a calibration curve of asphaltconcrete of a known mix design by measuring only one physical sample.The method involves obtaining a single sample of the known asphaltconcrete mix and air void content, and obtaining a dielectricmeasurement of the single sample. An “ideal dielectric” at a theoretical0% air void content is then computed using only that sample's measureddielectric value and void content. A dielectric vs. percent compactioncalibration curve can then be uniquely determined based only on onemeasured point and the calculated ideal dielectric value.

In some embodiments, the computing of the ideal dielectric is based onthe equation, derived by the inventor for this purpose.

$\epsilon = {\left( {\epsilon_{e} + \frac{f}{\frac{1}{\epsilon_{i} - \epsilon_{e}} + \frac{1 - f}{3\epsilon_{e}}} + \epsilon_{i} + \frac{1 - f}{\frac{1}{\epsilon_{e} - \epsilon_{i}} + \frac{f}{3\;\epsilon_{i}}}} \right)/2}$

where:

is the dielectric measurement of the single puck;

_(e) is the ideal dielectric of the asphalt mix with 0% voids;

_(i) is the dielectric of air; and

f is a volume fraction of air in the single puck.

In accordance with some embodiments of the disclosed technology, thereis provided a method for identifying a characteristic of a known asphaltmix. A calibration curve for the known asphalt mix is obtained using themethod of the disclosed technology described above. A second sample ofthe asphalt mix is obtained, the second sample having an unknown voidpercentage, and a second dielectric of the second sample is measured.The second dielectric is compared to the calibration curve, such thatwhen the second dielectric is on the calibration curve, a second airvoid percentage of the second sample is extracted from the calibrationcurve.

In some embodiments, when the second dielectric is off the calibrationcurve, this method can be used to identify the need to decompose andanalyze the second sample to understand what changed in the asphalt mixor in the environment surrounding the asphalt mix.

In some embodiments, the method can be used to identify some change inthe asphalt mix or in the environment, and to help adjust the asphaltmix to match the calibration curve.

In some other embodiments, the method further includes, in response toidentifying some change in the asphalt mix or in the environment,computing an updated calibration curve for the changed asphalt mix or atthe changed conditions.

In some embodiments, the method further includes comparing the extractedsecond air void percentage to an expected air void percentage, and whenthe extracted second air void percentage is distinct from the expectedair void percentage, decomposing and analyzing the second sample toidentify a change in the asphalt mix or in an environment surroundingthe asphalt mix.

In accordance with some embodiments of the disclosed technology, thereis provided a method for calculating a dielectric of an aggregateforming part of an asphalt concrete sample including the aggregate andat least one non-aggregate constituent. The method includes solving theequation of the disclosed technology discussed hereinabove using theideal dielectric of the asphalt, a known volume percent of thenon-aggregate constituents in the asphalt concrete sample, and adielectric of the non-aggregate constituents.

In accordance with some embodiments of the disclosed technology, thereis provided a method for identifying a characteristic of a known asphaltmix. The method includes using a dielectric measurement of a singlecalibration puck or core of the known asphalt concrete mix andgenerating a dielectric vs. percent compaction calibration curve for theknown asphalt mix. A second sample, which would be a puck or core, ofthe asphalt mix is obtained and a second dielectric of the second sampleis measured. The second sample has an unknown void percentage. Thesecond sample's dielectric is compared to the calibration curve, andwhen the second sample's dielectric is on the calibration curve, an airvoid percentage of the second sample is extracted from the calibrationcurve. When the second sample's dielectric is not on the calibrationcurve, the second sample is decomposed and analyzed to identify a changeto the known asphalt mix, and based on the measured dielectric of thesecond sample, and the identified change to the known asphalt mix, arevised dielectric vs. percent compaction calibration curve can begenerated for the asphalt mix following the change.

In some embodiments, the generating of the calibration curve for theknown asphalt mix includes obtaining the single calibration puck or coreof the known asphalt concrete mix, the single calibration puck or corehaving a known void percentage, and obtaining a dielectric measurementof the single calibration puck or core. Using only the dielectricmeasurement of the single calibration puck or core, components of theknown mix, and a dielectric of air, computing an ideal dielectric forthe asphalt concrete mix at 0% voids, and generating a dielectric vs.percent compaction calibration curve based only on the dielectricmeasurement of the single calibration puck or core and on the computedideal dielectric.

In accordance with some embodiments of the disclosed technology, thereis provided a method of projecting an expected dielectric of a knownasphalt mix at a specific void percentage. The method includes using adielectric measurement of a single calibration puck or core of the knownasphalt concrete mix, generating a dielectric vs. percent compactioncalibration curve for the known asphalt mix, and extracting from thecalibration curve for the known asphalt mix the expected dielectric forthe known asphalt mix at the specific void percentage.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic illustration of a plot of dielectric mixing curvesusing the modified bounds of embodiments of the disclosed technology.

FIG. 2 is a flow chart of an embodiment of a method for generating acalibration curve of asphalt concrete of a known mix, using a singlecalibration measurement, according to embodiments of the disclosedtechnology.

FIG. 3 is a flow chart of an embodiment of a method for using acalibration curve, such as the one generated using the method of FIG. 2,for identifying a characteristic of an asphalt mix, according toembodiments of the disclosed technology.

FIG. 4 is a high-level block diagram showing devices on whichembodiments of the disclosed technology may be carried out.

FIGS. 5A, 5B, and 5C are graphs comparing characteristics ofimplementation of the method of FIG. 2 according to embodiments of thedisclosed technology and prior art methods, using a first datasetgenerated from sample pucks.

FIG. 6 is a graph comparing characteristics of implementation of themethod of FIG. 2 according to embodiments of the disclosed technologyand prior art methods, using a second dataset generated from samplepucks.

FIG. 7 graph comparing characteristics of implementation of the methodof FIG. 2 according to embodiments of the disclosed technology and priorart methods, using a third dataset generated from sample pucks.

FIG. 8 is a graph comparing characteristics of implementation of themethod of FIG. 2 according to embodiments of the disclosed technologyand prior art methods, using a fourth dataset generated from samplepucks.

FIG. 9 is a graph comparing characteristics of implementation of themethod of FIG. 2 according to embodiments of the disclosed technologyand prior art methods, using a fifth dataset generated from samplepucks.

DETAILED DESCRIPTION OF EMBODIMENTS OF THE DISCLOSED TECHNOLOGY

The disclosed technology provides a method for generating a dielectricto air void curve, or calibration curve, for identifying an amount ofcompaction of asphalt concrete of a known mix, using a singlecalibration measurement.

Embodiments of the disclosed technology will become clearer in view ofthe following description and in view of the drawings.

The method of the disclosed technology is based on a modified form ofequations, originally derived to solve a different problem related tothe magnetic permeability limits of a mixture of two constituentmaterials possessing different magnetic permeabilities. The combinedmagnetic permeability of a mixture can vary depending on how the twoconstituents are randomly clustered together in the mixture. Certainareas of the mixture may comprise a slightly higher concentration of oneconstituent, compared to others. The measured magnetic permeability ofthe mixture thus varies, to some degree, depending on the variations inrandom clustering.

The Hashin-Shtrikman (HS) equations describe the maximum and minimummagnetic permeability of the mix for each mixing ratio. For example, iftwo different sands possessing different magnetic permeabilities were tobe combined 100 different times in a bucket at even ratios, and mixedwith a shovel, the measured magnetic permeability would be withinminimum and maximum values calculated using the HS equations.

In embodiments of the disclosed technology, the HS equations have beenmodified (M-HS equations) to compute the maximum and minimum dielectricvalues for mixtures comprising or containing constituents havingdifferent dielectrics. The inventor has found that the average of theminimum and maximum dielectric values obtained from the M-HS equationsdescribes the relationship of different effective dielectric values andassociated air void contents in asphalt exceedingly well, provided thatan accurate effective dielectric of the asphalt at “zero percent voidcontent” is substantially known or is known within an acceptabletolerance level.

Asphalt at zero percent void content is known as the Theoretical MaximumSpecific Gravity (Gmm), which is the maximum theoretical density of anasphalt mix assuming complete compaction without air voids.

The M-HS is given by:

$\epsilon = {\left( {\epsilon_{e} + \frac{f}{\frac{1}{\epsilon_{i} - \epsilon_{e}} + \frac{1 - f}{3\;\epsilon_{e}}} + \epsilon_{i} + \frac{1 - f}{\frac{1}{\epsilon_{e} - \epsilon_{i}} + \frac{f}{3\;\epsilon_{i}}}} \right)/2}$

Where:

=dielectric of asphalt core or puck;

_(e)=dielectric of corresponding asphalt mix with 0% voids (i.e. GMMdielectric);

_(i)=dielectric of air (1.0); and

f=volume fraction of air (which is % void/100)

FIG. 1 illustrates a plot of dielectric mixing curves using the averageH-S bounds. As seen in FIG. 1, for each dielectric and associated voidpercent, there is a specific Gmm dielectric. The inventor has discoveredthat the obtained curves, shown in FIG. 1, are substantially linear,particularly for low dielectrics. This allows the effective dielectricat 0% void, or at Gmm, to be extrapolated or extracted, for example byextending the relatively linear curve or by solving the equation for

_(e). In some embodiments of the disclosed technology, the Gmmdielectric can be calculated directly by inserting the known voidfraction (f) and associated dielectric (

) of a puck in the modified-HS equation and solving for

_(e).

Once the dielectric to void content curve is found, to determine theassociated air void content for any single asphalt sample one need onlylocate any measured dielectric on the calibration curve. Thus, accordingto the method of the disclosed technology, the calibration curve may befound using a single asphalt puck, enabling easier and more attainableadjustments for daily changes in the asphalt mix or in the ambientconditions.

Reference is now made to FIG. 2, which is a flow chart of an embodimentof a method for generating a calibration curve of asphalt concrete of aknown mix, using a single calibration measurement, according toembodiments of the disclosed technology.

At step 10, a known asphalt mix design is obtained, with knownproportions of known constituent materials. A portion of the asphalt mixis then compacted to generate a puck of known compaction percentage atstep 12. A dielectric measurement of the asphalt mix with the knowncompaction percentage is obtained at step 14 from the puck of step 12.The first dielectric measurement, extracted at step 14, is a control orbaseline measurement for the asphalt mix.

At step 16, the ideal dielectric for the asphalt mix at 100% compaction,or the Gmm dielectric for the asphalt mix, is determined, for example bysolving the M-HS equations discussed hereinabove to obtain a value ofthe Gmm dielectric. A dielectric vs. compaction percentage curve for theasphalt mix is generated, or determined, at step 18, based on themeasured dielectric for the obtained puck and the computed Gmmdielectric for the asphalt mix. As discussed hereinbelow, the curvegenerated in step 18 may function as a calibration curve, foridentifying the compaction level of any puck or sample of the asphaltmix.

Reference is now made to FIG. 3, which is a flow chart of an embodimentof a method for using a calibration curve, such as the one generatedusing the method of FIG. 2, for identifying a characteristic of anasphalt mix, according to embodiments of the disclosed technology. Forthe purpose of the description of FIG. 3, it is assumed that thecalibration curve for the asphalt mix is already known.

At step 30, a second puck of the known asphalt mix, having an unknowncompaction percentage, is obtained. For example, the second puck may beobtained by compacting asphalt obtained from a truck delivering asphaltto a paving job location. A second dielectric value corresponding to thesecond puck is measured at step 32. At step 34, the second measureddielectric is compared to the calibration curve.

If it is determined, at step 34, that the measured dielectric is outsideof the calibration curve (or sufficiently outside of the calibrationcurve to be considered more than a tolerance or measurement error), thismay be indicative of a change in the asphalt mix or in the environment.For example, the dielectric may be off of the expected curve if therehas been an unknown change to the mix design (e.g. more bitumen wasadded to the mix on a very cold day to make it more workable), if therehas been a change to the moisture level in the mix (e.g. if the mix hadbeen rained upon), or if there has been a change to the aggregate—to thesand or rock mineral content in the mix.

In such embodiments, at step 36, the second puck may be decomposed andanalyzed, in order to determine what has changed about the asphalt mixor about the environment. In some embodiments, at step 38, the asphaltmix is modified to compensate for changes identified during the analysisof step 36, so that the modified asphalt mix once again suits thecomputed curve. In some other embodiments, at step 40, a new calibrationcurve is computed for the asphalt mix, following the change identifiedat step 36, for example using the method of FIG. 2. The new calibrationcurve may then be used for all required computations using the asphaltmix following the change it had undergone.

If it is determined, at step 34, that the measured dielectric is on thecalibration curve, the percentage of air voids in the second puck may beextracted from the curve at step 42. In some embodiments, the extractedpercentage of air voids in the second puck is compared to an anticipated(theoretical) air void percentage value, at step 44. If the extractedpercentage of air voids in the second puck matches the anticipated airvoid percentage, the method terminates, as the air void percentage ofthe second puck is known. Otherwise, if extracted percentage of airvoids in the second puck does not match the anticipated air voidpercentage value, the flow may proceed to step 36, for analysis of thesecond puck in order to understand why the mismatch has occurred.

In some embodiments, the M-HS equations described hereinabove mayfurther be used to calculate the dielectric of one main component of anasphalt sample, assuming the dielectric and volume percentage of theother main component are known. For example, one can calculate thedielectric of the aggregate, if the dielectric and volume percentage ofthe bitumen are known. This yields key information to pavement engineersbecause anomalous aggregate dielectrics alert the operator to changes inthe aggregate composition and/or in the moisture content. For example,if the dielectric of the aggregate when it is dry is known, anexcessively high calculated aggregate dielectric from an asphalt sampleinfers the presence of moisture in the aggregate.

FIG. 4 shows a high-level block diagram of a device that may be used tocarry out the disclosed technology. Device 100 comprises a processor 105that controls the overall operation of the computer by executing thedevice's program instructions which define such operation. The device'sprogram instructions may be stored in a storage device 102 (e.g.,magnetic disk, database) and loaded into memory 103, when execution ofthe console's program instructions is desired. Thus, the device'soperation will be defined by the device's program instructions stored inmemory 103 and/or storage 102, and the console will be controlled byprocessor 105 executing the console's program instructions. A device 100also includes one, or a plurality of, input network interfaces forcommunicating with other devices via a network (e.g., the Internet). Thedevice 100 further includes an electrical input interface. A device 100also includes one or more output network interfaces 101 forcommunicating with other devices. Device 100 also includes input/output104, representing devices which allow for user interaction with acomputer (e.g., display, keyboard, mouse, speakers, buttons, etc.). Oneskilled in the art will recognize that an implementation of an actualdevice will contain other components as well, and that FIG. 4 is ahigh-level representation of some of the components of such a device,for illustrative purposes. It should also be understood by one skilledin the art that the method and devices depicted in FIGS. 1 through 3 maybe implemented on a device such as is shown in FIG. 4.

EXAMPLES

Reference is now made to the following examples, which, together withthe above description, illustrate the invention in a non-limitingfashion. Specifically, the examples provided herein demonstrate that themethod of generating a calibration curve as described hereinabove withrespect to FIG. 2, is functionally equivalent to prior art methods ofgenerating a calibration curve using analysis requiring many pucks of anasphalt mix.

Example 1

A dataset of 12 pucks obtained from Maine was used to generate a firstcalibration curve, shown in FIG. 5A. The calibration curve of FIG. 5A,which was generated using a least-squares fit line in accordance withprior art methods, plots the measured dielectric vs. the known voidpercentage for each puck in the dataset, and a linear approximation ofthe locations of the pucks is assumed to be the calibration curve. Thelinear approximation was then extended, as indicated by a dashed line inFIG. 5A, to extrapolate the corresponding dielectric value for a mixhaving 0% voids, or the Gmm, which was equal to 5.10.

For each of the 12 pucks in the Maine dataset, the dielectric at Gmm wascomputed using the method of the disclosed technology, as describedherein with respect to FIG. 2. FIG. 5B plots the dielectric at Gmm vs.measured % voids, as computed based on each of the pucks. The median Gmmvalue for all the pucks, indicated by a horizontal line in the graph ofFIG. 5B, is at a dielectric value of 5.13—within 0.03 of the valueobtained in FIG. 5A using a least-squares fit curve for the dielectricsand void percentage of each puck.

The median of individual Gmm dielectrics calculated in FIG. 5B was usedto generate a calibration curve for the mix, based on the mixing modeldescribed hereinabove, and specifically based on the modified H-Sequations. As seen in FIG. 5C, the curve computed using prior artmethods, based on measurement of multiple pucks, and the curve computedusing the method of the present invention, are very similar to eachother.

Example 2

A dataset of pucks obtained in NY in 2020 was used to generate twocalibration curves, shown in FIG. 6. The first calibration curve of FIG.6, is indicated by a solid line and was generated using a least-squaresfit line in accordance with prior art methods, plots the measureddielectric vs. the known void percentage for each puck in the dataset,and a linear approximation of the locations of the puck measurements isassumed to be the calibration curve.

A second calibration curve for the mix, indicated by a dashed line inFIG. 6, was generated using only the measured dielectric and known %voids of the of the puck having 6% voids, based on the mixing modeldescribed hereinabove, and specifically based on the M-HS equations. Asseen in FIG. 6, the curve computed using prior art methods, based onmeasurement of multiple pucks, and the curve computed using the methodof the present invention, are very similar to each other.

Example 3

A dataset of pucks obtained from Utah in 2019 was used to generate twocalibration curves, shown in FIG. 7. The first calibration curve of FIG.7, is indicated by a solid line and was generated using a least-squaresfit line in accordance with prior art methods, plots the measureddielectric vs. the known void percentage for each puck in the dataset,and a linear approximation of the locations of the puck measurements isassumed to be the calibration curve.

A second calibration curve for the mix, indicated by a dashed line inFIG. 7, was generated using only the measured dielectric and known %voids of the of the puck having 2.5% voids, based on the mixing modeldescribed hereinabove, and specifically based on the M-HS equations. Asseen in FIG. 7, the curve computed using prior art methods, based onmeasurement of multiple pucks, and the curve computed using the methodof the present invention, are very similar to each other, particularlyfor lower void percentages.

Example 4

A dataset of pucks obtained in 2018 from New York was used to generatetwo calibration curves, shown in FIG. 8. The first calibration curve wasgenerated using a least-squares fit line in accordance with prior artmethods, plots the measured dielectric vs. the known void percentage foreach puck in the dataset, and a linear approximation of the locations ofthe puck measurements is assumed to be the calibration curve.

A second calibration curve for the mix was generated using only themeasured dielectric and known % voids of the puck having 5% voids, basedon the mixing model described hereinabove, and specifically based on theM-HS equations. As seen in FIG. 8, the curve computed using prior artmethods, based on measurement of multiple pucks, and the curve computedusing the method of the present invention, are very similar to eachother.

Example 5

A dataset of pucks obtained in 2018 from Minnesota was used to generatetwo calibration curves, shown in FIG. 9. The first calibration curve ofFIG. 9 was generated using a least-squares fit line in accordance withprior art methods, plots the measured dielectric vs. the known voidpercentage for each puck in the dataset, and a linear approximation ofthe locations of the puck measurements is assumed to be the calibrationcurve.

A second calibration curve for the mix was generated using only themeasured dielectric and known % voids of the puck possessing 6.5% voids,based on the mixing model described hereinabove, and specifically basedon the M-HS equations. As seen in FIG. 9, the curve computed using priorart methods, based on measurement of multiple pucks, and the curvecomputed using the method of the present invention, are very similar toeach other.

Example 6

In order to determine the accuracy of the method of the disclosedtechnology relative to the method of the prior art for predicting thedielectric at a specific void percentage, not explicitly measured in apuck, the five datasets of pucks discussed hereinabove with respect toExamples 1-5 were compared to each other. For each of the datasets, theexpected dielectric for a puck having 8% void (or 92% compaction) wasextracted from the graph generated using the near fit squares of theprior art, and from the graph generated using the mixing model and themethod of the disclose technology. The 92% compaction value is ofparticularly important because paving contractor bonuses and/orpenalties often depend on the percentage of asphalt compacted aboveand/or below this threshold level. The results are shown in Table 1:

Linear Fit Mixing Model Dielectric for 8% Dielectric for 8% AbsolutePuck Dataset void void difference Maine 2018 4.575 4.611 0.037 NY 20206.226 6.232 0.006 Utah 2019 3.831 3.845 0.014 NY 2018 4.648 4.635 0.013Minnesota 2018 4.591 4.611 0.020

As clearly seen from Table 1, in all the puck datasets, the dielectricfor 8% void, projected based on the prior art methods and projectedbased on the method of the disclosed technology, are within 0.04 of oneanother, indicating that the method of the disclosed technology isequivalent, in terms of quality, to the prior art methods, while beingmuch simpler and much less time consuming, and overcoming thelimitations discussed in the background section hereinabove.

For purposes of this disclosure, the term “substantially” is defined as“at least 95% of” the term which it modifies.

Any device or aspect of the technology can “comprise” or “consist of”the item it modifies, whether explicitly written as such or otherwise.

When the term “or” is used, it creates a group which has within eitherterm being connected by the conjunction as well as both terms beingconnected by the conjunction.

While the disclosed technology has been taught with specific referenceto the above embodiments, a person having ordinary skill in the art willrecognize that changes can be made in form and detail without departingfrom the spirit and the scope of the disclosed technology. The describedembodiments are to be considered in all respects only as illustrativeand not restrictive. All changes that come within the meaning and rangeof equivalency of the claims are to be embraced within their scope.Combinations of any of the methods and apparatuses described hereinaboveare also contemplated and within the scope of the invention.

The invention claimed is:
 1. A method for identifying a characteristicof a known asphalt mix, the method comprising: using a dielectricmeasurement of a single calibration sample of the known asphalt concretemix, generating a dielectric vs. percent voids calibration curve for theknown asphalt mix; obtaining a sample of the asphalt mix, the samplehaving an unknown void percentage; measuring a dielectric of the sample;comparing the dielectric to the calibration curve; when the dielectricis on the calibration curve, extracting from the calibration curve anair void percentage of the sample; when the dielectric is not on thecalibration curve, decomposing and analyzing the sample to identify achange to the known asphalt mix; and based on the measured dielectric ofthe sample, and the identified change to the known asphalt mix,generating a revised dielectric vs. percent voids calibration curve forthe asphalt mix following the change.
 2. The method of claim 1, whereinthe generating of the calibration curve comprises: obtaining the singlecalibration sample of the asphalt mix, the single calibration samplehaving a known percent voids; obtaining a dielectric measurement of thesingle calibration sample; using only the dielectric measurement of thesingle calibration sample, computing an ideal dielectric for the asphaltmix at 0% voids; and generating the calibration curve based only on thedielectric measurement of the single sample and on the computed idealdielectric.
 3. The method of claim 2, wherein the computing of the idealdielectric is based on the equation$\epsilon = {\left( {\epsilon_{e} + \frac{f}{\frac{1}{\epsilon_{i} - \epsilon_{e}} + \frac{1 - f}{3\;\epsilon_{e}}} + \epsilon_{i} + \frac{1 - f}{\frac{1}{\epsilon_{e} - \epsilon_{i}} + \frac{f}{3\;\epsilon_{i}}}} \right)/2}$where:

is the dielectric measurement of the single calibration sample;

_(e) is the ideal dielectric of the asphalt mix with 0% voids;

_(i) is the dielectric of air; and f is a volume fraction of air in thesingle calibration sample.
 4. The method of claim 1, wherein thegenerating of the calibration curve for the known asphalt mix comprises:obtaining the single calibration sample of the known asphalt concretemix, the single calibration sample having a known percent voids;obtaining a dielectric measurement of the single calibration sample;using only the dielectric measurement of the single calibration sample,components of the known mix, and a dielectric of air, computing an idealdielectric for the asphalt concrete mix at 0% voids; and generating thecalibration curve based only on the dielectric measurement of the singlecalibration sample and on the computed ideal dielectric.
 5. The methodof claim 1, wherein the single calibration sample or the sample of theasphalt mix is a puck or a core extracted from paved asphalt.